Data streams provide enterprises the ability to monitor continually changing circumstances in real-time (e.g., based on data received from mobile devices, social media, and other sources). Processing this data in real-time allows enterprises to analyze business operations on an ongoing (and thus more relevant) basis. There is no (or minimal) lag between the data being generated/received, and the data being analyzed. Accordingly, enterprises may respond to business information promptly after the data is received.
Processing systems often execute tasks during analysis of data streams. These tasks transform the data streams. The tasks can be characterized as having certain properties in fixed categories. Encapsulating these properties as meta-data in the task itself is one way to ensure proper execution. However, encapsulating these properties as meta-data in the task itself can be tedious and is not system guaranteed.